Author: Eryk Walczak
Date: 2021-11-30

# Introduction

#### Eryk Walczak

#### 2021-11-30

PostcodesioR is an API wrapper for postcodes.io. It allows acquiring geographic information about the UK postcodes and geographic coordinates.

## Installation

    if (!require("devtools")) install.packages("devtools")
    devtools::install_github("ropensci/PostcodesioR")

## Lookup postcodes and outcodes

### Single postcode

Provide a postcode to obtain all available information

    library(PostcodesioR)

    lookup_result <- postcode_lookup("EC1Y8LX")

    #overview
    str(lookup_result)

    ## 'data.frame':    1 obs. of  35 variables:
    ##  $ postcode                       : chr "EC1Y 8LX"
    ##  $ quality                        : int 1
    ##  $ eastings                       : int 532544
    ##  $ northings                      : int 182128
    ##  $ country                        : chr "England"
    ##  $ nhs_ha                         : chr "London"
    ##  $ longitude                      : num -0.0909
    ##  $ latitude                       : num 51.5
    ##  $ european_electoral_region      : chr "London"
    ##  $ primary_care_trust             : chr "Islington"
    ##  $ region                         : chr "London"
    ##  $ lsoa                           : chr "Islington 023D"
    ##  $ msoa                           : chr "Islington 023"
    ##  $ incode                         : chr "8LX"
    ##  $ outcode                        : chr "EC1Y"
    ##  $ parliamentary_constituency     : chr "Islington South and Finsbury"
    ##  $ admin_district                 : chr "Islington"
    ##  $ parish                         : chr "Islington, unparished area"
    ##  $ admin_county                   : logi NA
    ##  $ admin_ward                     : chr "Bunhill"
    ##  $ ced                            : logi NA
    ##  $ ccg                            : chr "NHS North Central London"
    ##  $ nuts                           : chr "Haringey and Islington"
    ##  $ admin_district_code            : chr "E09000019"
    ##  $ admin_county_code              : chr "E99999999"
    ##  $ admin_ward_code                : chr "E05000367"
    ##  $ parish_code                    : chr "E43000209"
    ##  $ parliamentary_constituency_code: chr "E14000764"
    ##  $ ccg_code                       : chr "E38000240"
    ##  $ ccg_id_code                    : chr "93C"
    ##  $ ced_code                       : chr "E99999999"
    ##  $ nuts_code                      : chr "TLI43"
    ##  $ lsoa_code                      : chr "E01002704"
    ##  $ msoa_code                      : chr "E02000576"
    ##  $ lau2_code                      : chr "E09000019"

There is another function that returns the same data points but returns a list and allows optional parameters

    query_result <- postcode_query("EC1Y8LX")

    #overview
    str(query_result)

    ## List of 1
    ##  $ :List of 24
    ##   ..$ postcode                  : chr "EC1Y 8LX"
    ##   ..$ quality                   : int 1
    ##   ..$ eastings                  : int 532544
    ##   ..$ northings                 : int 182128
    ##   ..$ country                   : chr "England"
    ##   ..$ nhs_ha                    : chr "London"
    ##   ..$ longitude                 : num -0.0909
    ##   ..$ latitude                  : num 51.5
    ##   ..$ european_electoral_region : chr "London"
    ##   ..$ primary_care_trust        : chr "Islington"
    ##   ..$ region                    : chr "London"
    ##   ..$ lsoa                      : chr "Islington 023D"
    ##   ..$ msoa                      : chr "Islington 023"
    ##   ..$ incode                    : chr "8LX"
    ##   ..$ outcode                   : chr "EC1Y"
    ##   ..$ parliamentary_constituency: chr "Islington South and Finsbury"
    ##   ..$ admin_district            : chr "Islington"
    ##   ..$ parish                    : chr "Islington, unparished area"
    ##   ..$ admin_county              : NULL
    ##   ..$ admin_ward                : chr "Bunhill"
    ##   ..$ ced                       : NULL
    ##   ..$ ccg                       : chr "NHS North Central London"
    ##   ..$ nuts                      : chr "Haringey and Islington"
    ##   ..$ codes                     :List of 12
    ##   .. ..$ admin_district            : chr "E09000019"
    ##   .. ..$ admin_county              : chr "E99999999"
    ##   .. ..$ admin_ward                : chr "E05000367"
    ##   .. ..$ parish                    : chr "E43000209"
    ##   .. ..$ parliamentary_constituency: chr "E14000764"
    ##   .. ..$ ccg                       : chr "E38000240"
    ##   .. ..$ ccg_id                    : chr "93C"
    ##   .. ..$ ced                       : chr "E99999999"
    ##   .. ..$ nuts                      : chr "TLI43"
    ##   .. ..$ lsoa                      : chr "E01002704"
    ##   .. ..$ msoa                      : chr "E02000576"
    ##   .. ..$ lau2                      : chr "E09000019"

This function creates a nested list with the codes for administrative district, county, ward, parish, parliamentary constituency, CCG, and NUTS.

### Multiple postcodes

To query two or more postcodes, use `bulk_` functions.

    pc_list <- list(postcodes = c("PR3 0SG", "M45 6GN", "EX165BL"))
    bulk_lookup_result <- bulk_postcode_lookup(pc_list)

    #overview
    str(bulk_lookup_result[1])

    ## List of 1
    ##  $ :List of 2
    ##   ..$ query : chr "PR3%200SG"
    ##   ..$ result: NULL

If you want to work with data frame then the nested list created above can be turned into a data frame

    library(purrr)

    bulk_list <- lapply(bulk_lookup_result, "[[", 2)

    bulk_df <-
      map_dfr(bulk_list,
              `[`,
              c("postcode", "longitude", "latitude"))

Querying Scottish postcodes requires a separate function:

    scottish_lookup <- scottish_postcode_lookup("EH12NG")

    str(scottish_lookup)

    ## 'data.frame':    1 obs. of  3 variables:
    ##  $ postcode                                : chr "EH1 2NG"
    ##  $ scottish_parliamentary_constituency     : chr "Edinburgh Central"
    ##  $ scottish_parliamentary_constituency_code: chr "S16000104"

### Outward code lookup

Provide an outcode to obtain geolocation data for the centroid of the specified outcode:

    ocl <- outward_code_lookup("E1")

    #overview
    str(ocl)

    ## List of 10
    ##  $ outcode       : chr "E1"
    ##  $ longitude     : num -0.0595
    ##  $ latitude      : num 51.5
    ##  $ northings     : int 181613
    ##  $ eastings      : int 534741
    ##  $ admin_district:List of 3
    ##   ..$ : chr "Hackney"
    ##   ..$ : chr "City of London"
    ##   ..$ : chr "Tower Hamlets"
    ##  $ parish        :List of 3
    ##   ..$ : chr "Hackney, unparished area"
    ##   ..$ : chr "City of London, unparished area"
    ##   ..$ : chr "Tower Hamlets, unparished area"
    ##  $ admin_county  : list()
    ##  $ admin_ward    :List of 14
    ##   ..$ : chr "Shadwell"
    ##   ..$ : chr "Spitalfields & Banglatown"
    ##   ..$ : chr "St Dunstan's"
    ##   ..$ : chr "Portsoken"
    ##   ..$ : chr "Stepney Green"
    ##   ..$ : chr "Weavers"
    ##   ..$ : chr "Whitechapel"
    ##   ..$ : chr "Bow West"
    ##   ..$ : chr "Bethnal Green"
    ##   ..$ : chr "Bishopsgate"
    ##   ..$ : chr "Hoxton East & Shoreditch"
    ##   ..$ : chr "Tower"
    ##   ..$ : chr "Aldgate"
    ##   ..$ : chr "St Peter's"
    ##  $ country       :List of 1
    ##   ..$ : chr "England"

## Reverse geocoding

Provide latitude and longitude to obtain geographic information. Different levels of aggregation are available, i.e. postcode or outcode.

### Single postcode

    rev_geo <- reverse_geocoding(0.127, 51.507)

    # overview
    str(rev_geo[1])

    ## List of 1
    ##  $ :List of 25
    ##   ..$ postcode                  : chr "SE28 8NH"
    ##   ..$ quality                   : int 1
    ##   ..$ eastings                  : int 547715
    ##   ..$ northings                 : int 180780
    ##   ..$ country                   : chr "England"
    ##   ..$ nhs_ha                    : chr "London"
    ##   ..$ longitude                 : num 0.127
    ##   ..$ latitude                  : num 51.5
    ##   ..$ european_electoral_region : chr "London"
    ##   ..$ primary_care_trust        : chr "Bexley"
    ##   ..$ region                    : chr "London"
    ##   ..$ lsoa                      : chr "Bexley 001D"
    ##   ..$ msoa                      : chr "Bexley 001"
    ##   ..$ incode                    : chr "8NH"
    ##   ..$ outcode                   : chr "SE28"
    ##   ..$ parliamentary_constituency: chr "Erith and Thamesmead"
    ##   ..$ admin_district            : chr "Bexley"
    ##   ..$ parish                    : chr "Bexley, unparished area"
    ##   ..$ admin_county              : NULL
    ##   ..$ admin_ward                : chr "Thamesmead East"
    ##   ..$ ced                       : NULL
    ##   ..$ ccg                       : chr "NHS South East London"
    ##   ..$ nuts                      : chr "Bexley and Greenwich"
    ##   ..$ codes                     :List of 12
    ##   .. ..$ admin_district            : chr "E09000004"
    ##   .. ..$ admin_county              : chr "E99999999"
    ##   .. ..$ admin_ward                : chr "E05011232"
    ##   .. ..$ parish                    : chr "E43000194"
    ##   .. ..$ parliamentary_constituency: chr "E14000696"
    ##   .. ..$ ccg                       : chr "E38000244"
    ##   .. ..$ ccg_id                    : chr "72Q"
    ##   .. ..$ ced                       : chr "E99999999"
    ##   .. ..$ nuts                      : chr "TLI51"
    ##   .. ..$ lsoa                      : chr "E01000469"
    ##   .. ..$ msoa                      : chr "E02000065"
    ##   .. ..$ lau2                      : chr "E09000004"
    ##   ..$ distance                  : num 38.9

### Multiple postcodes

To reverse geocode multiple values use the function underneath. The result is a nested list, which might be a bit intimidating, but it allows storing unequal number of elements.

    # create a list with the coordinates
    geolocations_list <- structure(
     list(
     geolocations = structure(
     list(
     longitude = c(-3.15807731271522, -1.12935802905177),
     latitude = c(51.4799900627036, 50.7186356978817),
     limit = c(NA, 100L),
     radius = c(NA, 500L)),
     .Names = c("longitude", "latitude", "limit", "radius"),
     class = "data.frame",
     row.names = 1:2)),
     .Names = "geolocations")

    bulk_rev_geo <- bulk_reverse_geocoding(geolocations_list)

    bulk_rev_geo[[1]]$result[[1]]

    ## $postcode
    ## [1] "CF24 2BT"
    ##
    ## $quality
    ## [1] 1
    ##
    ## $eastings
    ## [1] 319675
    ##
    ## $northings
    ## [1] 176305
    ##
    ## $country
    ## [1] "Wales"
    ##
    ## $nhs_ha
    ## [1] "Cardiff and Vale University Health Board"
    ##
    ## $longitude
    ## [1] -3.158076
    ##
    ## $latitude
    ## [1] 51.47998
    ##
    ## $european_electoral_region
    ## [1] "Wales"
    ##
    ## $primary_care_trust
    ## [1] "Cardiff and Vale University Health Board"
    ##
    ## $region
    ## NULL
    ##
    ## $lsoa
    ## [1] "Cardiff 038D"
    ##
    ## $msoa
    ## [1] "Cardiff 038"
    ##
    ## $incode
    ## [1] "2BT"
    ##
    ## $outcode
    ## [1] "CF24"
    ##
    ## $parliamentary_constituency
    ## [1] "Cardiff South and Penarth"
    ##
    ## $admin_district
    ## [1] "Cardiff"
    ##
    ## $parish
    ## [1] "Splott"
    ##
    ## $admin_county
    ## NULL
    ##
    ## $admin_ward
    ## [1] "Splott"
    ##
    ## $ced
    ## NULL
    ##
    ## $ccg
    ## [1] "Cardiff and Vale University Health Board"
    ##
    ## $nuts
    ## [1] "Cardiff and Vale of Glamorgan"
    ##
    ## $codes
    ## $codes$admin_district
    ## [1] "W06000015"
    ##
    ## $codes$admin_county
    ## [1] "W99999999"
    ##
    ## $codes$admin_ward
    ## [1] "W05000879"
    ##
    ## $codes$parish
    ## [1] "W04001005"
    ##
    ## $codes$parliamentary_constituency
    ## [1] "W07000080"
    ##
    ## $codes$ccg
    ## [1] "W11000029"
    ##
    ## $codes$ccg_id
    ## [1] "7A4"
    ##
    ## $codes$ced
    ## [1] "W99999999"
    ##
    ## $codes$nuts
    ## [1] "TLL22"
    ##
    ## $codes$lsoa
    ## [1] "W01001874"
    ##
    ## $codes$msoa
    ## [1] "W02000404"
    ##
    ## $codes$lau2
    ## [1] "W06000015"
    ##
    ##
    ## $distance
    ## [1] 1.567236

The list above is not the most common way of storing files. It’s more likely that a data frame will be used to store the geodata. In that case, it has to be turned into a list of a specific format required by the API:

    geolocations_df <- structure(
      list(
        longitude = c(-3.15807731271522, -1.12935802905177),
        latitude = c(51.4799900627036, 50.7186356978817),
        limit = c(NA, 100L),
        radius = c(NA, 500L)),
      .Names = c("longitude", "latitude", "limit", "radius"),
      row.names = 1:2,
      class = "data.frame")

    geolocations_df

    ##   longitude latitude limit radius
    ## 1 -3.158077 51.47999    NA     NA
    ## 2 -1.129358 50.71864   100    500

    # turn a data frame into a list
    geolocations_df2list <- list(geolocations_df)

    # add a list name
    names(geolocations_df2list) <- "geolocations"

    # display correct input for the function
    geolocations_df2list

    ## $geolocations
    ##   longitude latitude limit radius
    ## 1 -3.158077 51.47999    NA     NA
    ## 2 -1.129358 50.71864   100    500

Common usage of this function might be extracting particular variables. You can extract one variable like this:

    # extract one postcode
    bulk_rev_geo[[1]]$result[[8]]$postcode

    ## [1] "CF24 2AL"

But more likely you will want more than one result. After all, that’s the point of using a bulk function:

    # function to extract variables of interest
    extract_bulk_geo_variable <- function(x) {
      bulk_results <- lapply(bulk_rev_geo, `[[`, "result")
      sapply(unlist(bulk_results, recursive = FALSE), `[[`, x)
    }

    # define the variables you need
    variables_of_interest <- c("postcode", "latitude", "longitude")

    # return a data frame with the variables
    data.frame(
      sapply(variables_of_interest, extract_bulk_geo_variable))

    ##    postcode  latitude longitude
    ## 1  CF24 2BT 51.479976 -3.158076
    ## 2  CF24 2ED 51.479691 -3.158688
    ## 3  CF24 2AA 51.480209 -3.159062
    ## 4  CF24 5NW  51.47936 -3.158478
    ## 5  CF24 2AJ 51.480682 -3.158526
    ## 6  CF24 2AH 51.480552 -3.158912
    ## 7  CF24 2DZ 51.480105 -3.156798
    ## 8  CF24 2AL  51.48083 -3.158141
    ## 9  PO33 1PS 50.718856 -1.129271
    ## 10 PO33 1PT 50.718573 -1.128467
    ## 11 PO33 1PX 50.717878 -1.127136
    ## 12 PO33 1QB 50.717046 -1.129826
    ## 13 PO33 1QD 50.717191 -1.127843
    ## 14 PO33 1PU 50.718465 -1.126032
    ## 15 PO33 1PZ 50.716247 -1.127932
    ## 16 PO33 1QR  50.71574 -1.125998
    ## 17 PO33 1PB 50.721022 -1.133719
    ## 18 PO33 1PR 50.721486 -1.133187
    ## 19 PO33 1FS 50.717285  -1.12372
    ## 20 PO33 1QP 50.715694 -1.124911
    ## 21 PO34 5AP 50.721536 -1.124476
    ## 22 PO33 1PY 50.715218 -1.125104

### Single outcode

    out_rev_geocode <- outcode_reverse_geocoding("-3.15", "51.47")
    # overview
    str(out_rev_geocode[1])

    ## List of 1
    ##  $ :List of 10
    ##   ..$ outcode       : chr "CF99"
    ##   ..$ longitude     : num -3.16
    ##   ..$ latitude      : num 51.5
    ##   ..$ northings     : int 174588
    ##   ..$ eastings      : int 319421
    ##   ..$ admin_district:List of 1
    ##   .. ..$ : chr "Cardiff"
    ##   ..$ parish        :List of 1
    ##   .. ..$ : chr "Butetown"
    ##   ..$ admin_county  : list()
    ##   ..$ admin_ward    :List of 1
    ##   .. ..$ : chr "Butetown"
    ##   ..$ country       :List of 1
    ##   .. ..$ : chr "Wales"

## Generate random entries

### Postcodes

Generates a list with a random UK postcode and corresponding geographic information:

    # without restrictions
    random_postcode()

    ## $postcode
    ## [1] "N1 8FP"
    ##
    ## $quality
    ## [1] 1
    ##
    ## $eastings
    ## [1] 531630
    ##
    ## $northings
    ## [1] 183943
    ##
    ## $country
    ## [1] "England"
    ##
    ## $nhs_ha
    ## [1] "London"
    ##
    ## $longitude
    ## [1] -0.103385
    ##
    ## $latitude
    ## [1] 51.53905
    ##
    ## $european_electoral_region
    ## [1] "London"
    ##
    ## $primary_care_trust
    ## [1] "Islington"
    ##
    ## $region
    ## [1] "London"
    ##
    ## $lsoa
    ## [1] "Islington 020B"
    ##
    ## $msoa
    ## [1] "Islington 020"
    ##
    ## $incode
    ## [1] "8FP"
    ##
    ## $outcode
    ## [1] "N1"
    ##
    ## $parliamentary_constituency
    ## [1] "Islington South and Finsbury"
    ##
    ## $admin_district
    ## [1] "Islington"
    ##
    ## $parish
    ## [1] "Islington, unparished area"
    ##
    ## $admin_county
    ## NULL
    ##
    ## $admin_ward
    ## [1] "St Mary's"
    ##
    ## $ced
    ## NULL
    ##
    ## $ccg
    ## [1] "NHS North Central London"
    ##
    ## $nuts
    ## [1] "Haringey and Islington"
    ##
    ## $codes
    ## $codes$admin_district
    ## [1] "E09000019"
    ##
    ## $codes$admin_county
    ## [1] "E99999999"
    ##
    ## $codes$admin_ward
    ## [1] "E05000379"
    ##
    ## $codes$parish
    ## [1] "E43000209"
    ##
    ## $codes$parliamentary_constituency
    ## [1] "E14000764"
    ##
    ## $codes$ccg
    ## [1] "E38000240"
    ##
    ## $codes$ccg_id
    ## [1] "93C"
    ##
    ## $codes$ced
    ## [1] "E99999999"
    ##
    ## $codes$nuts
    ## [1] "TLI43"
    ##
    ## $codes$lsoa
    ## [1] "E01002794"
    ##
    ## $codes$msoa
    ## [1] "E02000573"
    ##
    ## $codes$lau2
    ## [1] "E09000019"

A randomly generated postcode can also belong to a particular outcode:

    # restrict to an outcode
    random_postcode("N1")

    ## $postcode
    ## [1] "N1 6SB"
    ##
    ## $quality
    ## [1] 1
    ##
    ## $eastings
    ## [1] 533320
    ##
    ## $northings
    ## [1] 183129
    ##
    ## $country
    ## [1] "England"
    ##
    ## $nhs_ha
    ## [1] "London"
    ##
    ## $longitude
    ## [1] -0.079365
    ##
    ## $latitude
    ## [1] 51.53134
    ##
    ## $european_electoral_region
    ## [1] "London"
    ##
    ## $primary_care_trust
    ## [1] "City and Hackney Teaching"
    ##
    ## $region
    ## [1] "London"
    ##
    ## $lsoa
    ## [1] "Hackney 027B"
    ##
    ## $msoa
    ## [1] "Hackney 027"
    ##
    ## $incode
    ## [1] "6SB"
    ##
    ## $outcode
    ## [1] "N1"
    ##
    ## $parliamentary_constituency
    ## [1] "Hackney South and Shoreditch"
    ##
    ## $admin_district
    ## [1] "Hackney"
    ##
    ## $parish
    ## [1] "Hackney, unparished area"
    ##
    ## $admin_county
    ## NULL
    ##
    ## $admin_ward
    ## [1] "Hoxton East & Shoreditch"
    ##
    ## $ced
    ## NULL
    ##
    ## $ccg
    ## [1] "NHS North East London"
    ##
    ## $nuts
    ## [1] "Hackney and Newham"
    ##
    ## $codes
    ## $codes$admin_district
    ## [1] "E09000012"
    ##
    ## $codes$admin_county
    ## [1] "E99999999"
    ##
    ## $codes$admin_ward
    ## [1] "E05009377"
    ##
    ## $codes$parish
    ## [1] "E43000202"
    ##
    ## $codes$parliamentary_constituency
    ## [1] "E14000721"
    ##
    ## $codes$ccg
    ## [1] "E38000255"
    ##
    ## $codes$ccg_id
    ## [1] "A3A8R"
    ##
    ## $codes$ced
    ## [1] "E99999999"
    ##
    ## $codes$nuts
    ## [1] "TLI41"
    ##
    ## $codes$lsoa
    ## [1] "E01001777"
    ##
    ## $codes$msoa
    ## [1] "E02000371"
    ##
    ## $codes$lau2
    ## [1] "E09000012"

## Places

You can also generate a random place, specified by an OSGB code, with corresponding geographic information:

    random_place()

    ##                   code            name_1 name_1_lang name_2 name_2_lang
    ## 1 osgb4000000074563063 Titchfield Common        NULL   NULL        NULL
    ##         local_type outcode county_unitary county_unitary_type district_borough
    ## 1 Other Settlement    PO14      Hampshire              County          Fareham
    ##   district_borough_type     region country longitude latitude eastings
    ## 1              District South East England  -1.26567   50.852   451789
    ##   northings min_eastings min_northings max_eastings max_northings
    ## 1    106088       451073        105634       452928        107139

## Postcode validation

This function can validate a UK postcode:

    postcode_validation("EC1Y8LX") # actual UK postcode

    ## [1] TRUE

    postcode_validation("XYZ") # incorrect UK postcode

    ## [1] FALSE

## Autocomplete postcodes

Find the potential candidates for a postcode if you only know the beginning characters

    postcode_autocomplete("EC1")

    ##    postcode
    ## 1  EC1A 1AA
    ## 2  EC1A 1AH
    ## 3  EC1A 1AZ
    ## 4  EC1A 1BB
    ## 5  EC1A 1DN
    ## 6  EC1A 1DU
    ## 7  EC1A 1HQ
    ## 8  EC1A 1TA
    ## 9  EC1A 1TB
    ## 10 EC1A 1TF

It defaults to 10 candidates, but can be changed by specifying the `limit` argument.

## Find nearest postcodes or outcodes

Provide a postcode to get a list of the nearest postcodes:

    near_pc <- nearest_postcode("EC1Y8LX")

    #overview
    str(near_pc[1])

    ## List of 1
    ##  $ :List of 25
    ##   ..$ postcode                  : chr "EC1Y 8LX"
    ##   ..$ quality                   : int 1
    ##   ..$ eastings                  : int 532544
    ##   ..$ northings                 : int 182128
    ##   ..$ country                   : chr "England"
    ##   ..$ nhs_ha                    : chr "London"
    ##   ..$ longitude                 : num -0.0909
    ##   ..$ latitude                  : num 51.5
    ##   ..$ european_electoral_region : chr "London"
    ##   ..$ primary_care_trust        : chr "Islington"
    ##   ..$ region                    : chr "London"
    ##   ..$ lsoa                      : chr "Islington 023D"
    ##   ..$ msoa                      : chr "Islington 023"
    ##   ..$ incode                    : chr "8LX"
    ##   ..$ outcode                   : chr "EC1Y"
    ##   ..$ parliamentary_constituency: chr "Islington South and Finsbury"
    ##   ..$ admin_district            : chr "Islington"
    ##   ..$ parish                    : chr "Islington, unparished area"
    ##   ..$ admin_county              : NULL
    ##   ..$ admin_ward                : chr "Bunhill"
    ##   ..$ ced                       : NULL
    ##   ..$ ccg                       : chr "NHS North Central London"
    ##   ..$ nuts                      : chr "Haringey and Islington"
    ##   ..$ codes                     :List of 12
    ##   .. ..$ admin_district            : chr "E09000019"
    ##   .. ..$ admin_county              : chr "E99999999"
    ##   .. ..$ admin_ward                : chr "E05000367"
    ##   .. ..$ parish                    : chr "E43000209"
    ##   .. ..$ parliamentary_constituency: chr "E14000764"
    ##   .. ..$ ccg                       : chr "E38000240"
    ##   .. ..$ ccg_id                    : chr "93C"
    ##   .. ..$ ced                       : chr "E99999999"
    ##   .. ..$ nuts                      : chr "TLI43"
    ##   .. ..$ lsoa                      : chr "E01002704"
    ##   .. ..$ msoa                      : chr "E02000576"
    ##   .. ..$ lau2                      : chr "E09000019"
    ##   ..$ distance                  : int 0

You can also use outcodes:

    near_outcode <- nearest_outcode("EC1Y")

    # overview
    str(near_outcode[2])

    ## List of 1
    ##  $ :List of 10
    ##   ..$ outcode       : chr "EC2Y"
    ##   ..$ longitude     : num -0.0935
    ##   ..$ latitude      : num 51.5
    ##   ..$ northings     : int 181777
    ##   ..$ eastings      : int 532373
    ##   ..$ admin_district:List of 2
    ##   .. ..$ : chr "Islington"
    ##   .. ..$ : chr "City of London"
    ##   ..$ parish        :List of 2
    ##   .. ..$ : chr "Islington, unparished area"
    ##   .. ..$ : chr "City of London, unparished area"
    ##   ..$ admin_county  : list()
    ##   ..$ admin_ward    :List of 6
    ##   .. ..$ : chr "Coleman Street"
    ##   .. ..$ : chr "Aldersgate"
    ##   .. ..$ : chr "Bunhill"
    ##   .. ..$ : chr "Bassishaw"
    ##   .. ..$ : chr "Clerkenwell"
    ##   .. ..$ : chr "Cripplegate"
    ##   ..$ country       :List of 1
    ##   .. ..$ : chr "England"

Or longitude and latitude

    near_ll <- nearest_outcode_lonlat(0.127, 51.507)

    #overview
    str(near_ll[1])

    ## List of 1
    ##  $ :List of 10
    ##   ..$ outcode       : chr "DA18"
    ##   ..$ longitude     : num 0.136
    ##   ..$ latitude      : num 51.5
    ##   ..$ northings     : int 179422
    ##   ..$ eastings      : int 548389
    ##   ..$ admin_district:List of 1
    ##   .. ..$ : chr "Bexley"
    ##   ..$ parish        :List of 1
    ##   .. ..$ : chr "Bexley, unparished area"
    ##   ..$ admin_county  : list()
    ##   ..$ admin_ward    :List of 2
    ##   .. ..$ : chr "Slade Green & Northend"
    ##   .. ..$ : chr "Thamesmead East"
    ##   ..$ country       :List of 1
    ##   .. ..$ : chr "England"

## Find places

Provide a name of a place of interest. You can specify the number of results (default is 10):

    place_query_result <- place_query("Hills", limit = 11)

    # overview
    str(place_query_result[1])

    ## List of 1
    ##  $ :List of 21
    ##   ..$ code                 : chr "osgb4000000074574731"
    ##   ..$ name_1               : chr "Berwick Hills"
    ##   ..$ name_1_lang          : NULL
    ##   ..$ name_2               : NULL
    ##   ..$ name_2_lang          : NULL
    ##   ..$ local_type           : chr "Suburban Area"
    ##   ..$ outcode              : chr "TS3"
    ##   ..$ county_unitary       : chr "Middlesbrough"
    ##   ..$ county_unitary_type  : chr "UnitaryAuthority"
    ##   ..$ district_borough     : NULL
    ##   ..$ district_borough_type: NULL
    ##   ..$ region               : chr "North East"
    ##   ..$ country              : chr "England"
    ##   ..$ longitude            : num -1.21
    ##   ..$ latitude             : num 54.6
    ##   ..$ eastings             : int 451459
    ##   ..$ northings            : int 518602
    ##   ..$ min_eastings         : int 450839
    ##   ..$ min_northings        : int 517640
    ##   ..$ max_eastings         : int 451963
    ##   ..$ max_northings        : int 519361

You can also find a place using an OSGB code:

    place_lookup_result <- place_lookup("osgb4000000074544700")

    # overview
    str(place_lookup_result)

    ## List of 21
    ##  $ code                 : chr "osgb4000000074544700"
    ##  $ name_1               : chr "Cutler Heights"
    ##  $ name_1_lang          : NULL
    ##  $ name_2               : NULL
    ##  $ name_2_lang          : NULL
    ##  $ local_type           : chr "Suburban Area"
    ##  $ outcode              : chr "BD4"
    ##  $ county_unitary       : NULL
    ##  $ county_unitary_type  : NULL
    ##  $ district_borough     : chr "Bradford"
    ##  $ district_borough_type: chr "MetropolitanDistrict"
    ##  $ region               : chr "Yorkshire and the Humber"
    ##  $ country              : chr "England"
    ##  $ longitude            : num -1.72
    ##  $ latitude             : num 53.8
    ##  $ eastings             : int 418830
    ##  $ northings            : int 431785
    ##  $ min_eastings         : int 418487
    ##  $ min_northings        : int 431541
    ##  $ max_eastings         : int 419040
    ##  $ max_northings        : int 432041

## Terminated postcodes

You might end up having terminated postcodes in your data set. These are postcodes that are no longer active. UK postcodes can change so it’s worth checking whether used postcodes are still active. If you need more information about when a particular postcode was terminated use:

    terminated_postcode("E1W 1UU")

    ##   postcode year_terminated month_terminated longitude latitude
    ## 1  E1W 1UU            2015                2 -0.073732 51.50801